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Characterization and prediction of some engineering properties of polymer-Clay/Silica hybrid nanocomposites through ANN and regression models

机译:通过ANN和回归模型的聚合物 - 粘土/二氧化硅杂交纳米复合材料一些工程性能的表征与预测

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The search from time immemorial for stronger, lighter and more durable materials used in construction and tools continues to this day. This urge to discover, invent and synthesize new materials has resulted in innumerable kinds of alloys, plastics and composites owing to the very exacting demands from different industries like aerospace, automobile, chemical, marine and so on. Glass fibers reinforced in polymers have received considerable attention during the last century. Studies conducted during the last decade reveal that adding small amounts of foreign particles (like clay or silica) of nanosize significantly improves the engineering properties of the polymers. This study presents the effect of reinforcing epoxy polymer with Halloysite nanoclay on mechanical properties. In the present work the clay in terms 1, 2 and 3 percent by weight was surface treated with a suitable silane agent. The hybrid nanocomposite was prepared by the hand lay-up technique. Characterization of the nanoclay was done by X-ray diffraction and Scanning electron microscopy. ASTM standards have been employed for investigating hardness, dynamic mechanical properties, wear, damping and post underwater shock. All the tests were done for both silica and clay as reinforcement materials. Analysis and Results have been presented for impact of nanoclay reinforcement on all the parameters. Radial basis function network, a tool of ANN, is employed to predict the above outcomes. Mathematical regression models have been employed for theoretical prediction. Comparative study reveals that ANN Tool predictions have better agreement with measured values than the other model. Thus, it can be confidently concluded that ANN Tool can be used to predict the properties of hybrid nanocomposites before actual manufacture. This will result in considerable savings in terms of project time, effort and cost.
机译:从时代高雅的搜索更强大,打火机和更耐用的材料在施工和工具中持续到这一天。这种促使发现,发明和合成新材料,由于航空航天,汽车,化学,海洋等不同行业的需求非常严格,塑料和复合材料导致了无数种子,塑料和复合材料。在聚合物中加强的玻璃纤维在上世纪也受到了相当大的关注。在过去十年中进行的研究表明,添加少量的纳米型外来颗粒(如粘土或二氧化硅)显着改善了聚合物的工程性质。该研究介绍了加强环氧聚合物与霍氏铁纳米粘土对机械性能的影响。在本工作中,用合适的硅烷处理,用合适的硅烷处理1,2和3重量%的粘土。通过手敷设技术制备杂化纳米复合材料。通过X射线衍射和扫描电子显微镜进行纳米粘土的表征。 ASTM标准已用于调查硬度,动态机械性能,磨损,阻尼和水下震动。所有测试都是用于二氧化硅和粘土作为加强材料。纳米粘土增强对所有参数的影响,已经提出了分析和结果。径向基函数网络是ANN的工具,用于预测上述结果。已经采用了数学回归模型来理论预测。比较研究表明,ANN工具预测与比其他模型的测量值更好地达成了更好的协议。因此,可以自信地得出结论,ANN工具可用于预测实际制造前的杂化纳米复合材料的性质。这将在项目时间,努力和成本方面得到相当大的节省。

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